Abstract
Since agricultural environments are mostly in unstructured feature information, in order to facilitate agricultural robots to better adapt to environmental change problems in agricultural environments, this paper proposes a robot system architecture for agricultural fields scouting. The article proposes: 1) the analysis of some existing field agricultural robots; 2) a novel approach that first constructs a map using the Rtabmap SLAM technique and second employs a particle filter-based Monte Carlo method to estimate the robot's position post-hoc with a loopback detection process; 3) the pipeline of robot works (which is developing), including its architecture, taking into account selected hardware and software components. Firstly, the hardware architecture of the robot and its required sensors are considered, then the AMCL route planning algorithm is applied. The depth camera+lidar+RTK approach is used for the robot's map construction, the simulation model of robot route planning by ROS, the robot design by SolidWorks, and finally the required sensors and hardware structure parts are analyzed and summarized. Based on the considered project, it is planned to create a field agricultural scouting robot, which will become part of the implementation of a digital twin in crop production.
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Mitrofanova, O., Blekanov, I., Sevostyanov, D., Zhang, J., Mitrofanov, E. (2023). Development of a Robot for Agricultural Field Scouting. In: Ronzhin, A., Sadigov, A., Meshcheryakov, R. (eds) Interactive Collaborative Robotics. ICR 2023. Lecture Notes in Computer Science(), vol 14214. Springer, Cham. https://doi.org/10.1007/978-3-031-43111-1_17
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DOI: https://doi.org/10.1007/978-3-031-43111-1_17
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